Tech is key for climate adaptation, but don’t ignore local knowledge: CSTEP’s Indu Murthy

Venkatesh Kannaiah: Tell us about climate adaptation technologies that are relevant in an Indian context.

Indu Murthy: Early warning systems (EWS), climate-resilient agri-tech, and cool roofs and passive cooling for buildings are the most relevant technologies in an Indian context.

The India Meteorological Department has been providing district-level heat and flood alerts using satellite data and IoT sensors, and information is delivered through SMS. Such early warning systems are a good example of climate adaptation tech.

EWS has helped save lives in cyclones that normally hit the coast of Odisha. However, it is a different matter whether such warnings are leading to coordinated community action. Also, though the warnings are timely, when it comes to flood alerts, one must be cautious, as it might not be meticulously mapped to potential flood zones or flood-prone zones. It might be heavy rain alerts, which could be extrapolated to flood alerts.

As for agritech, we find that organisations such as the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and startups like SatSure and Cropin use remote sensing and machine learning to deliver crop-specific advisories to farmers in rainfed agriculture. This helps in addressing the issues of both adaptation and resilience.

However, when you’re dependent on remote sensing and machine learning, the requirements are extremely context-specific and localised when it comes to cropping. There are many variables, from soil moisture to what happens in adjoining farms. It may not be very relevant for the kind of small parcels of land that we have.

For building cooling, there are reflective roof coatings combined with green roofs and cross-ventilation design, which offer a low-cost, accessible way to counter urban heat island effects in Indian cities.

Venkatesh Kannaiah: Could you tell us about your work at CSTEP?

Indu Murthy: In the climate adaptation space, CSTEP works with both state and city governments and generates data and evidence to support decision-making and policy formulation.

We look at the panchayat, district, and state levels to analyse how climate is changing and understand what those changes mean on the ground. It could be heavy rainfall leading to floods, droughts, sea-level rise, heat waves, and so on.

We also try to understand the vulnerabilities and potential risks that emerge when hazards, exposure, and vulnerability intersect. For example, a flood in a relatively well-off area versus a flood in low-income settlements can have very different consequences. This is where exposure, adaptive capacity, and vulnerability determine how impacts are experienced. We generate this kind of evidence and use it to inform decision-making.

We have helped states like Kerala, Tamil Nadu, Karnataka, and Chhattisgarh develop climate action plans. Our city-level engagement is just beginning. We will be working in Assam and are likely to work in Nagpur, particularly on heat-related challenges.

On heat adaptation,  we have carried out granular mapping of blue, green, and grey infrastructure in Bengaluru. Based on that, we are developing an ecosystem-based adaptation planning tool. The idea is to identify where green cover and other adaptation measures can be introduced most effectively. It is a solution-oriented planning tool. It helps identify where different adaptation measures could potentially be implemented and incorporates the cost-benefit analyses of various interventions.

Venkatesh Kannaiah: Tell us about climate tech adaptations that have not worked globally and why?

Indu Murthy: Several climate tech interventions have struggled globally. Carbon Capture and Storage is one such intervention. In the 2010s, it was being referred to as a silver bullet, but most large-scale projects failed due to massive capital costs. There is also the cost of compressing carbon and a lack of viable carbon dioxide storage sites. Carbon emissions need to be compressed, put into containers, and stored in safe places. This process itself consumes a lot more energy. Then there is the question of utilisation, which is another challenge. In India, underground storage also appears difficult due to certain geologic conditions.

Second is the innovation of solar panels on water bodies, also called ‘floating solar’, which was adopted across Southeast Asia. However, this has in many cases disrupted aquatic ecosystems, reduced oxygen levels, and impacted the livelihoods of fishing communities.

Finally, many smart city climate tech initiatives like sensor networks, flood sensors, and real-time dashboards have failed to translate into policy action or community benefit, with data being collected but with no follow-up action.

Venkatesh Kannaiah: Tell us about the climate adaptation/mitigation tech ecosystem in India.

Indu Murthy: India’s climate adaptation and mitigation tech ecosystem is growing, but unevenly. On the research side, there are institutions like CSTEP and many others, such as the National Institute of Urban Affairs, and the IITs are producing credible science around urban heat, water stress, and agriculture.

The startup space has also seen genuine growth over the past five years, with companies working across air quality, climate risk, environmental monitoring, agri-climate analytics, and climate tech. There is, however, a lag in clean energy funding.

There are also some gaps in translating research into policy, and having funding specifically for climate adaptation rather than mitigation.

Venkatesh Kannaiah: Tell us about heat adaptation tech in urban areas.

Indu Murthy: Several emerging areas are shaping urban heat adaptation. Low-energy wearable cooling vests and phase-change material clothing are being developed for outdoor workers who bear the greatest heat burden.

AI-powered urban heat island mapping is now using satellite thermal data and street-level sensors to identify intra-city heat pockets at fine resolution. Digital twin models are being used to simulate the cooling effect of tree canopies, water bodies, and permeable surfaces before committing large amounts to infrastructure development.

Tech platforms to locate, manage, and monitor public cooling centres during heat waves are being piloted in states like Rajasthan. On the regulatory side, reforms to the Energy Conservation Building Code (ECBC) aim to mandate design and cool material standards in new construction.

But cutting across all of these is the critical issue of equity in cooling to ensure adaptation solutions reach low-income settlements, street vendors, and construction workers, and not just those with access to air-conditioned spaces.

Venkatesh Kannaiah: What needs to be done in Indian cities to address the issue of urban flooding?

Indu Murthy: Addressing urban flooding in Indian cities requires action on multiple fronts. Most cities lack ward-level flood risk maps, making drone mapping, LiDAR surveys, and hydrology modelling an urgent first step.

The flood maps will also need to be area-specific because hydrology is dependent on the soil, its permeability, infrastructure, land use, land cover, and terrain. Cities like Bengaluru have already done such hydrology flood modelling, but since cities are growing fast, it needs to be done repeatedly, given the infrastructure changes.

We need stormwater master plans that treat drainage as core infrastructure rather than an afterthought. We need to incorporate the features of a ‘sponge city’ with permeable pavements, retention ponds, and wetland restoration.

Real-time flood forecasting integrated with drainage operations, combining IoT sensors, ML-based flow prediction, and automated pump management, can further reduce response times. However, no tech solution will work without addressing encroachment on floodplains, as nearly every Indian city has informal settlements occupying natural drainage corridors, making land use reform essential.

Finally, community-level preparedness, neighbourhood alert networks, and local flood wardens often outperform expensive dashboards and must be built alongside the technological investment.

Venkatesh Kannaiah: What gaps exist in government systems, infrastructure, or community preparedness on climate adaptation tech?

Indu Murthy: Significant gaps exist across government systems, infrastructure, and community preparedness.

At the institutional level, urban local bodies, water boards, disaster management authorities, and climate cells continue to operate in silos without shared data or coordination platforms.

Most infrastructure, be it roads, bridges, drains, or dams, is designed for historical climate conditions rather than projected future ones, and the absence of standardised climate vulnerability indices leaves decision-makers without actionable data.

On the infrastructure side, aging drainage, water supply, and power systems remain under-maintained and untested against climate stress, while green infrastructure such as urban forests and wetlands is largely absent from city master plans.

At the community level, risk communication remains top-down and is often distrusted. Vulnerable groups are routinely excluded from adaptation planning, and local knowledge about historical flooding, water sources, and heat refuges is rarely documented or integrated into tech solutions.

Venkatesh Kannaiah: Tell us about tools being developed for better adoption of adaptation solutions.

Dr Indu Murthy: A range of tools is being developed to improve the adoption of climate adaptation solutions. Decision support platforms like NIUA’s Climate Centre are designed to help municipalities choose and sequence interventions.

Participatory GIS and mobile-based co-design tools, drawing on approaches like Ushahidi, enable communities to map their own vulnerabilities and feed local knowledge into planning processes.

On the finance side, platforms like Climo are helping banks and insurers price climate risk into loans and insurance products, unlocking private capital for adaptation. Monitoring, reporting, and verification platforms for tracking adaptation outcomes are still nascent globally but growing in importance.

Finally, capacity-building MOOCs and simulation tools are helping urban planners and city officials understand and act on climate risk without needing to be climate scientists themselves.

Venkatesh Kannaiah: Tell us about the success stories of government-community interaction that tackled climate change.

Dr Indu Murthy: The Ahmedabad Heat Action Plan is a globally cited model that uses a tiered alert system, coordinates cooling centres, trains ASHA workers to identify heat stress, and communicates via SMS. It has measurably reduced heat-related mortality, with its success rooted in multi-agency coordination and community health worker integration.

Odisha’s disaster management model offers another compelling story. The state transformed from recording over 10,000 cyclone deaths in 1999 to near-zero mortality in recent major cyclones, achieved through community cyclone shelters, trained local volunteers, satellite-linked early warning systems, and robust last-mile communication, making the State Disaster Management Authority a model for other states.

Following the catastrophic 2018 floods, Kerala launched the Rebuild Kerala Initiative, a structured climate-resilient reconstruction programme that integrated risk mapping, community consultation, and went further by legislating wetland conservation and floodplain zoning.

Venkatesh Kannaiah: How is AI changing the field of climate adaptation?

Indu Murthy: It is early days. Machine Learning models from initiatives like ClimateAI are producing localised, high-resolution climate projections far faster than traditional models, which is critical for city-level planning.

In agriculture, AI-powered crop recommendation and pest and disease early warning systems, such as Microsoft’s FarmBeats and SatSure in India, are delivering advisory support at scale. Google’s Flood Hub now issues flood forecasts covering parts of India, significantly improving early warning times.

The key question for India, however, is whether these AI solutions can be made easy to interpret, validate, and accessible to state governments and communities, rather than remaining within global tech platforms.